Optical Computing Node Error Recovery via Process Image Comparison
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Solution Overview
Problem
Existing data processing systems face challenges in efficiently detecting and resolving errors associated with failed jobs in optical computing nodes, leading to processing delays and failures.
Innovation Solution
The system employs a processing manager that generates process images for job processing across multiple optical computing nodes. It detects failures, compares metadata with reference images, identifies root causes, and resolves inconsistencies to re-deploy corrected process images, enhancing error detection and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional error detection and resolution methods are used in optical computing nodes, then the system can identify failed jobs, but processing delays occur due to manual intervention and lack of automated root cause analysis
Solution Approach 1:
The system performs preliminary actions by generating process images with embedded metadata and maintaining an image repository of reference process images before failures occur. When a failure is detected, the pre-prepared reference images enable immediate comparison and root cause identification without manual intervention, thus reducing processing delays while maintaining productivity
Solution Approach 2:
The system implements feedback by monitoring optical computing nodes for failures, comparing failed process images against reference images in the repository, identifying root causes through metadata analysis, and automatically re-deploying corrected process images. This closed-loop feedback mechanism eliminates manual intervention and reduces processing delays while maintaining high job processing throughput
2Productivity
If process images are re-deployed after failure without verification, then processing can resume quickly, but data security and integrity are compromised
Solution Approach 1:
The system uses Zero Knowledge Proof (ZKP) logic as an intermediary verification mechanism between the failed process image and its re-deployment. The ZKP logic cryptographically verifies the integrity and security of the process image without exposing sensitive data, enabling quick resumption of processing while maintaining data security and integrity
Solution Approach 2:
The system performs preliminary security verification using ZKP logic before re-deploying corrected process images. This pre-verification step ensures data security is validated in advance, allowing rapid resumption of processing without compromising reliability, as the security check is already completed before deployment
Data Source
AI summary
A processor receives a command to process a job, generates a plurality of process images, and deploys the process images on a plurality of optical computing nodes. The processor detects that a first process image has failed at a first optical computing node, and in response, identifies a first reference process image corresponding to the first process image. The processor determines a root cause associated with the failed first process image based on comparing the first process image to the first reference process image. The processor resolves the root cause and re-deploys the first process image at the first computing node or a second computing node.